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Related Experiment Video

Updated: Jun 11, 2025

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS
11:00

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS

Published on: May 20, 2013

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Modular, Scalable, and Customizable LC-HRMS for Exposomics.

Vinicius Verri Hernandes1,2, Benedikt Warth3,4

  • 1Department of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna, Vienna, Austria.

Methods in Molecular Biology (Clifton, N.J.)
|October 1, 2024
PubMed
Summary
This summary is machine-generated.

This study presents a versatile liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method for non-targeted exposomics analysis. The workflow enhances toxicant identification in human samples using data-dependent acquisition and inclusion lists.

Keywords:
Analytical toxicologyBiomonitoringData-dependent analysisEnvironmental and food contaminantsExposome researchHigh-resolution mass spectrometryUntargeted metabolomics and exposomics

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Area of Science:

  • Environmental Chemistry
  • Analytical Chemistry
  • Toxicology

Background:

  • Exposomics research aims to comprehensively measure all exogenous and endogenous small molecules in biological samples.
  • Accurate and sensitive analytical methods are crucial for non-targeted detection of a wide range of xenobiotics.
  • Existing workflows may require optimization for broad toxicant profiling in human matrices.

Purpose of the Study:

  • To describe a flexible reversed-phase liquid chromatography-high-resolution mass spectrometry (LC-HRMS) workflow for non-targeted exposomics.
  • To enable semi-targeted analysis of toxicants using data-dependent acquisition (DDA) and inclusion lists.
  • To provide expected retention times for over 160 diverse xenobiotics in human plasma and serum.

Main Methods:

  • Development of a multi-purpose LC-HRMS method.
  • Implementation of data-dependent acquisition (DDA) for data acquisition.
  • Utilized toxicant inclusion lists for enhanced identification of xenobiotics.
  • Analysis of human plasma and serum samples.

Main Results:

  • Established a robust LC-HRMS workflow for high-quality exposomics data.
  • Generated expected retention times for >160 xenobiotics, aiding in compound identification.
  • Demonstrated the utility of DDA combined with inclusion lists for semi-targeted toxicant analysis.

Conclusions:

  • The described LC-HRMS workflow serves as a valuable tool for exposomics research and education.
  • The method is adaptable for specialized research needs, including integration with data-independent acquisition (DIA).
  • This approach facilitates comprehensive toxicant profiling and understanding of environmental exposures.